Recent technological innovations have transformed biomedical research into a highly interdisciplinary and computationally intensive endeavor. A scientific workforce armed with the requisite quantitative skills is needed to achieve new breakthroughs in biomedical research. The Short Course on Systems Genetics addresses the need for a growing interdisciplinary workforce in biomedical research by training biologists and quantitative scientists in the statistical and computational methods of genetic data analysis. Participants will (1) develop an understanding of genetic and statistical principles relevant to th analysis of complex phenotypes and disease; (2) critically evaluate quantitative data from large-scale genetic and molecular biological studies; (3) develop appropriate study designs using contemporary molecular and statistical genetic approaches; and (4) develop professional relationships that promote interdisciplinary research efforts. This will be accomplished through an intensive immersion experience in an environment that brings together students and faculty with diverse backgrounds but with a common interest in quantitative approaches to biology. The overall goal of the course is to train new scientists and re-train established investigators in the use of mathematical tools for the analysis of complex phenotypes and systems. Our six-day residential Short Course on Systems Genetics provides a balance of didactic and practical instruction with ample opportunities for interactions among participants and course faculty. Past participants have highlighted the value of professional exchanges, collegiality, and networking provided by the unique setting of the course. Hands-on computational training is also highly valued by course participants and will be a focus area for growth and development of the course in coming years. The impact of the residential course is necessarily limited. Therefore we propose to significantly expand our outreach by developing new online content. Systems Genetics Online will be maintained as an open-access website dedicated to the course. Content will include data and software scripts to support hands-on computational training; quantitative genetics and R training primers for use by participants before and during the course; and course lectures in video and pdf formats. Using this two-fold approach we aim to disseminate better understanding of genetic and statistical principles for biologists grappling with statistics and fo statisticians grappling with modern biological applications relevant to the analysis of complex disease-related phenotypes.